Abstract

An attempt to create a unifying and universal interpretation of (socio)economic events through history is presented. These are termed the Seven Waves of Code. It is argued that the most important technological advances have to do with computing and coding technologies, and most critically, the ability to compute and transfer data. This process is discussed back to the time period of the 11th and 12th centuries, where the first coding technology emerged, the printer. This printing technology (and all subsequent waves) led to a more rapid dissemination of ideas throughout the world, which results in growth periods of decreasing periodicity (more rapid innovation cycles), which end in social conflicts that catalyze new innovation. The paper will delve into aspects of science, technology, philosophy, history, and economics, with a spin towards technological forecasting and universal understandings. It develops an idea that not only are there economic cycles, but there exists an economic super-cycle, and its end is rapidly approaching.

Introduction

Virtually all physical and social systems in this world around us have been observed to undergo forms of cyclic behavior. This is found to occur on the atomic and molecular scale.[1] It occurs in biological systems (composed of arrays of molecular materials), with the most notable example being the circadian rhythm, with observational origins dating back to the 4th century BC.[2] The circadian rhythm of both plants[3] and animals[4] is directly linked to solar events,[5] like many other examples given here in this paper, which is also linked to much of the early work regarding economic cycles. Biological rhythms and cyclic behavior are found throughout the whole spectrum of these systems, ranging from single cells to networks of tissue and organs, to populations on the whole.[6] The same phenomenon is omnipresent in non-biological material systems, such as the cyclical behavior observed for soil and sand,[7] as well as concrete[8] due to the cyclic stresses imposed upon each of them that resemble the typical operating parameters in everyday life. These behaviors similarly extend to non-biological polymer[9] and alloy-based systems,[10] referred to as shape memory alloys. Like circadian rhythms, these cyclical stresses imposed on these materials are a result of solar cycles. In addition to observations for the microcosm, cyclical behavior is also observed for a variety of macrocosmic phenomena. Numerous studies on the properties and cycles of solar systems have been conducted through the years. Such examples include cyclical time intervals between outbursts of dwarf-nova systems,[11] more general phenomena related to solar polar fields[12] including effects on magnetic fields related to solar events.[13]

These cyclic phenomena also find their way into the theories and understandings of early cosmology. This lineage of thought as it is related to modern scientific theory found its origin with the physicist Richard Tolman, who became interested in the work of Alexander Friedmann[14] and explored these principles in a 1934 book entitled Relativity, Thermodynamics and Cosmology.[15] According to previously published work[16] by Tolman, he noted that a cyclical universe contradicted the classical (19th century) understanding of the second law of thermodynamics. He argued; however, that in relativity theory processes could take place without any increase in entropy. He postulated that the model of Einstein’s periodic universe could expand and contract reversibly without an increase in entropy.

Figure 1.  Tolman’s illustration of two cycles of an oscillating universe, with the later cycle being greater than the earlier one. The quantity  e 1/2 g  represents the radius of the curvature.[15]

Figure 1. Tolman’s illustration of two cycles of an oscillating universe, with the later cycle being greater than the earlier one. The quantity e1/2g represents the radius of the curvature.[15]

Tolman’s analysis showed that identical cycles and periods, described by sinusoidal functions would have to be replaced with a pattern in which each new cycle becomes greater than the previous cycle (Figure 1), both with respect to the period and the maximum value of the curvature radius. This is able to fit with a present model of universal inflation in the early cosmos, theorized to require curvature perturbations, which has given rise to a concept known as the curvaton model thought at present to be a strong mathematical fit according to analyses of inflation in the early cosmos.[17] Mathematical studies in recent years have continued exploring cyclical behavior in the early cosmologies of the universe.[18] These ideas have moved into other thought processes such as conformal cyclic cosmology[19] and loop quantum cosmology.[20]

While I have given a few examples of cyclic phenomena occurring at scales studied in the natural sciences, ranging from atomic and subatomic particles to biological systems, to universal or cosmological understandings, the area that perhaps has been studied most extensively in this regard are the social sciences, with a particular emphasis on economics.

A modern origin of cyclical philosophy in humanities can be traced back to the French philosopher Giambattista Vico, who was a contemporary of Rene Descartes, and also critical of Descartes non-humanistic approach to his work.[21] He defined this approach as a geometrical one, that has later been argued to be the origin of what we today define as nihilism.[22] He made an attempt to unify the social sciences (humanities) by exploring the idea of historical cycles that give rise to societies, but which also contribute to their ultimate demise. This line of thought was articulated in his work La Scienza Nuova.[23] He emphasized three stages of progress, the (1) age of gods, the (2) age of heros, and the (3) age of men. Vico’s ideas originate back to works of Plato, expressed in his work Republic,[24] in ‘The Myth of Er’. Similarly, the stoicism school of ancient greek philosophy discusses the idea[25] that analysis of Nitchzsche’s work later made famous, through the term eternal recurrence.[26] This posit states that the universe contains no beginning or end, but rather is a cyclical process, occurring indefinitely. This is a similar idea expressed in the eastern religious philosophies of Hinduism, Buddhism, and Jainism.[27] These ideas have similarly taken a modern spin through recent studies of early cosmology, being intimately related to particular inflation theories which suppose that the universe can undergo eternal recurrence through an eternal inflation mechanism.[28] This is also related to the idea of conformal cyclic cosmology noted above.

One of the first attempts to directly pin economic data to cycles in business and markets was written by Sir William Hershel, who in 1801[29] attempted to correlate solar phenomenon of sunspots with the price of wheat. These writings evidently inspired Robert Everest, Hyde Clarke, and later William Stanley Jevons to study these phenomena in greater detail. Robert Everest looked at the probability of famines in India occurring in a cyclical fashion, by analyzing the price of wheat between 1763 and 1835.[30] He concluded from the data that cycles could be observed, having a duration of ten or eighteen years. Hyde Clarke continued these studies in his paper Physical Economy - A Preliminary Inquiry into the Physical Laws Governing the Periods of Famines and Panics.[31] Much of this early work was attempting to tie economic data to the naturally occurring solar cycles of approximately 11 to 12 years.[32] It was later observed that there are additional super cycles that occur, with the most famous of these being the Gleissberg cycle, comprising 8 individual solar cycles than span approximately 88 years.[33] Additionally, there are a variety of other super cycles that have been proposed such as 200 year de Vries cycle,[34] a 1000 year cycle,[35] and the 2400 year Hallstatt cycle.[36]

William Stanley Jevon was perhaps the first to study cyclical behavior in a more systematic fashion, eventually culminating in the work The Periodicity of Commercial Crises and its Physical Explanation.[37] In the paper he surmises that the trade depression in England at that time was based on a “long series of events of the same kind, occurring with remarkable regularity at intervals of about ten years.” Though he conceded that his access to the data was limited as best, only allowing him to probe these effects for the better part of a half-century. Many additional individuals contributed to these understandings over the next twenty to thirty years, including the work of Wesley Mitchell[38] and Dennis Robertson[39] who explored business and trade cycles in the United States and United Kingdom, respectively. In addition to this prevailing thought emerging in western economics, these ideas found their way into eastern economic thought, with perhaps the most notable early proponents of the ideas being the Ukrainian economist Mikhail Tugan-Baranovsky and Sergei Alekseevich Pervushin.[40] Pervushin published a work that was, to that date, the most comprehensive analysis of cyclical behavior in the Russian economy.[41] His work provided a critique to Tugan-Baransovsky’s work, placing a greater emphasis on fluctuations in agriculture. The observations of Pervushin were noted and endorsed by the economist Joseph Schumpeter, who made economic cycles popular amongst western market analysts in the middle to late 20th century. It shouldn’t be too much of a surprise then, that arguably the most famous economist to take to the analysis of economic cycles, Nikolai Kondratiev, wrote a biography of Tugan-Baranovsky.[42]

Nikolai Kondratiev was born in 1892 in a province north of Moscow. He studied at the University of St. Petersburg before the 1917 Russian Revolution led by Mikhail Tugan- Baranovsky and Alexander Sergeyevich Lappo-Danilevsky. His early studies were in the area of agricultural economics and statistics, with an emphasis on the problem of food supply.[43] After the revolution, Kondratiev pursued academic research. It was through this path, and observations related to technological changes in agriculture that he came to publish his most prominent work regarding economic cycles, even into recent times, entitled The Major Economic Cycles.[44] The author argues that it was the most recognized example because of its attempts to unify the theories that had been building up across the past century, which cumulatively showed a distinct correlation between various physical phenomena and cyclic economic behavior. While this is certainly a profound work that has captured the imagination of economists to this day, the general framework that had been built up looking at the economy more as a natural system was abolished in western thought with the advancement of Keynesian policies after World War II. The Keynesian model places far less emphasis on economic processes as natural or physical properties, instead focusing on human activity and behaviors through a demand-side model. This replaces the more holistic approach of looking at both supply and demand as complementary to one another.[45]

Since the emergence of Keynesian economics, the study and interpretation of naturally occurring cyclical phenomenon can be argued to have been relegated more to the fringes of economic thought, especially in western countries. Instead, a sizable body of literature has come about that is focused on business cycles primarily as a result of human activity. A key passage that illustrates this point is

“Keynesian macroeconomics destroys the classical dichotomy by abandoning the assumption that wages and prices adjust instantly to clear markets. This approach is motivated by the observation that many nominal wages are fixed by long-term labor contracts and many product prices remain unchanged for long periods of time. Once the inflexibility of wages and prices is admitted into a macroeconomic model, the classical dichotomy and the irrelevance of money quickly disappear.”[46]

This model, as described above, puts an emphasis on long-term labor contracts as playing the critical role in the equilibrium of markets. It also, from a more philosophical point-of-view, supposes that the actor is entirely separate from the system. This philosophical path has led the study of economics as a whole away from the understanding that markets and, indeed the economy in its entirety, could possibly be a part of a system of natural laws governed by the universe. This can be demonstrated through the increased specialization of research looking at phenomena related to business cycles, such as the cyclical behavior of interest rates,[47] the cyclical behavior of job and worker flows,[48] the magnitude and cyclical behavior of financial market frictions,[49] heterogeneous job-matches and the cyclical behavior of labor turnover,[50] the cyclical behavior of debt and equity finance,[51] and countless other examples that place a clear emphasis on human behavior over more naturally occurring phenomenon. The author argues that this is a very similar sequence of events as has been unfolding in the study of the natural sciences over the past century, where there has been a stream of publications exploring the increasing specialization of the field, with little effort to attempt to unify those understandings and interpretations. In fact, recent work in particle physics (standard model) makes assumptions on the existence of particles based entirely on their presumed existence from theoretical decay pathways.[52]

Considering how cyclic phenomena have been shown to permeate all aspects of life in this universe, it is argued that researchers should consider focusing on the notion that global and macroeconomic principles could be based on natural law as opposed to discrete phenomenon of human activity and behavior. This paper will attempt to provide a unifying model based on the work of early researchers, with particular focus on the unifying theory brought forth by Nikolai Kondratiev. The work will explore the analysis of technological adoption and markets over the past century, and correlate those observations to both the work of Kondratiev and more recently Daniel Smihula who suggested that economic waves are becoming shorter in duration.[53]

Figure 2.  Shows the general wave-function associated with the rise and fall of each wave of coding technology. Begins somewhere in the 11th and 12th century, leading up to present day.

Figure 2. Shows the general wave-function associated with the rise and fall of each wave of coding technology. Begins somewhere in the 11th and 12th century, leading up to present day.

A General Theorem

The figure above illustrates the theory behind this present work, illustrated as a general (non-derived) wave-function. The wave behaves in a way that can be described as a reverse damped sine wave function, where each cycle (total market behavior) results in a period that is compressed (to roughly half of the previous cycle) and an amplitude that is approximately twice that of the previous cycle. This hypothesis will be discussed through observations made in the next section, where market behavior and technological adoption has a strong correlation with the current hypothesis. This is not designed to be a comprehensive analysis of the data, but merely a starting point to generate discussion, eventually leading to more comprehensive data analyses.

Some Observations on Markets and Technological Adoption (1900-2018)

An overview of historical views on economic cycles and long-waves was detailed in the introduction section. Since Nikolai Kondratiev introduced the concept of long-waves in 1925, there has been a large body of research conducted on furthering those understandings. These have been quite well-studied in the understanding of business cycles.[54]

Joseph Schumpeter was a renowned Austrian born economist who wrote extensively about business cycles and economic rhythms.[55] During this era, most research was focused on the idea of long-waves, and only in the past five decades has the term Kondratiev waves emerged, partly because of the light shined on the concept by Schumpeter. He is also attributed as popularizing the concept of “creative destruction”[56] which is a fundamental principle in long waves and economic cycles, which are described in their proper historical context in the following section. The analysis of business cycles and long-waves have, like all areas of science, have taken a much more specialized approach in recent decades, with researchers probing these effects as they relate to economic crises,[57] behavioral[58] or social[59] economics, fiscal[60] and monetary[61] policy, but most often linking these observations to technological innovation.[62]

Figure 3.  Shows the inflation adjusted values (blue) of the Dow Jones between 1914 and 2018. The black line represents the proposed wave-function highlighted in the last section. The inset image is a theoretical model of inflation in the universe showing a qualitative plot of how the scale factor evolves as a function of the conformal time, 𝙩.[28]

Figure 3. Shows the inflation adjusted values (blue) of the Dow Jones between 1914 and 2018. The black line represents the proposed wave-function highlighted in the last section. The inset image is a theoretical model of inflation in the universe showing a qualitative plot of how the scale factor evolves as a function of the conformal time, 𝙩.[28]

As has been discussed, over the past decades there has been a shift away from the idea of more universal understandings to the specialized work that is currently being performed. Nevertheless, there have been researchers who continue exploring the phenomenon of Kondratiev waves (i.e. long waves, K-waves) in recent years, looking at their consequences in more specialized contexts, such as behaviors related to energy consumption and price indices,[64] social conflicts and clusters of innovation,[65] as well as linking the first long wave to the technological innovation of the printer.[66] Additionally, the notion has been brought forth that the waves are becoming shorter in duration as time moves forward,[53] correlating with observations made by the author through parameters outlined below.

Figure 3 shows the inflation adjusted values (blue) for the Dow Jones between the years 1914 and 2018.[67] Assuming the model presented in the previous section, we observe that the absolute maximum value obtained during each wave is approximately double that of the previous wave. This is emphasized by the presence of the black line. The inset image in the figure is of a theoretical mathematical model of cyclic inflation in cosmology. It had been shown in previous work[68] how a class of closed universal models, as we go back in time (cycles), results in the universe spending increased durations in the thermal Hagedorn phase, where entropy remains constant. As a result, in the infinite past the universe asymptotes to an almost periodic evolution with short time periods (string time scale and energy densities) and constant but non-zero entropy, which satisfies Tolman’s entropy problem discussed in a previous section.[28] It is argued that this process could have influenced researchers to conclude that economic cycles occur in approximately ten year cycles. They were simply not able to observe a super-cycle in their reference point of time, due to the lower entropy of the informational transfer in a technological paradigm. More simply put, the most recent cycles beginning with the third wave result in a much higher entropy in the economic system due to more rapid flow and decentralization of information, catalyzed by the technological advancement of the telegraph (i.e. nearly immediate transfer of information) then subsequent technologies.

This figure is only meant to serve as an illustrative example. The Dow Jones does not adequately encompass all of the major asset classes, and this exercise would be more fruitful with the analysis and averaging of all large asset classes (US equities, worldwide equities, US bonds, worldwide bonds, real estate, cash equivalents, commodities). This is an objective of future studies and culminate in the second of the three paper series. In addition to market behavior, technological adoption and innovation is a critical component in explaining long-wave phenomenon. The figure below details the technological adoption rates of various technologies since the beginning of the 20th century. Analyzing the time for adoption through the various cycles, it can be surmised that the rate of adoption is decreasing in periodicity, as suggested by recent work exploring Kondratiev waves.[53] When looking at the adoption of technology connected to the third wave (telegraph/analytical engines) of innovation, such as the telephone and the automobile, full adoption took between 75 and 100 years (Note: The figure assumes adoption to 90%). This is in line with the proposal that states that the third wave took a little over a century to be completed. During the fourth wave (electromechanical computers) various products such as the dryer, air conditioning, and dishwasher took roughly 50 years for adoption, again matching the hypothesis. It is noted that these devices relied heavily on the advancement of electromechanical devices. The fifth wave (internet) saw the rise of PCs and gaming consoles, where mass adoption took between 25 and 30 years, again matching the proposal presented herein. The sixth wave (cloud/ mobile) witnesses the emergence of cellphones, and in particular smartphones and tablets which all took between 8 and 15 years for mass adoption. The seventh wave is hypothesized to be artificial intelligence. We are already observing the rapid adoption of AI devices, with projections of full adoption (>90%) occurring before 2022-2023.[69] The third paper in the series will explore technological adoption through detailed patent analyses and investment numbers, specifically through the study of technological S- curves.[71]

Figure 4.  Illustrates technological adoption rates of various technologies since 1900.[70]

Figure 4. Illustrates technological adoption rates of various technologies since 1900.[70]

Discussion

While the bulk of the published literature discusses the long-wave phenomenon occurring as a result of innovation emerging in different technological areas, this theory supposes that the technological origin of an economic super-cycle is related to a single type of technology. Namely, it is theorized that coding technologies have had there hand in every economic cycle dating back to the 11th to 12th century. This is not to say that observations of cyclical behavior according to various technologies can not emerge alongside this phenomenon. Indeed, their has been ample evidence provided that these types of cycles can and do occur in one form or another.

This theory specifically explores the impacts of coding technologies. The first example (or wave) of coding technology is postulated to be the printer, which undoubtably led to significant changes in the dynamics of monetary systems for humanity. While Gutenberg is often credited as being the inventor of the printer,[72] in reality its origins date back to far-east Asia in the 11th and 12th centuries.[73] The wood-block printer gave rise to the first Fiat currencies in China in the middle of the 11th century. The printer, as the author argues, can be defined as an early coding technology because it directly encoded information (printed) in a fashion that allowed ideas to spread more quickly than possible without it. It decentralized information flow in a way not possible before the invention, limiting central control of information that catalyzed import social events such as the Reformation and Renaissance. Each successive advance in coding technology played a role in furthering the ability to compute and transfer information, at ever increasing rates.

The whole theory surrounds this single important idea.

“As an idea (or data) is able to spread at a faster rate, resulting from innovations in coding and causing the dissemination of those ideas, innovation cycles occur at faster rates. You can not build on an idea if you are unaware of the idea.”

Attempts to loosely correlate data with macroeconomic events were made in the previous section, having explored the growth of technologies through parameters such as market behaviors and technological adoption. Like the long-waves presented by Nikolai Kondratiev, this theory also identifies and correlates the most significant social events occurring over the past millennia with the proposed wave-function. A major turning point in the first wave was the black death outbreak that ravaged Europe during the 14th century.[74] After this period of despair in Europe, another turning point could be defined as the fall of Constantinople, occurring in the year 1453.[75] This time period also coincided with the rise of printing in Europe, which had mostly been relegated to the far east up until that point. This sequence of events eventually led to major changes in Europe, most significant of those having been the Protestant Reformation[76] and Renaissance,[77] each of which has argued to have resulted from the development of the movable-type printing press. The end of the first wave was marked by some of the last outbreaks of Black Plague in western Europe during the late 16th and early 17th century.[78] These outbreaks also coincided with major contractions of Western European economies at that time.[79] It was not only western Europe; however, who was experiencing significant downturns in their economic state. The Ottoman Empire had a major financial collapse in the early 17th century, from which it never was able to fully recover.[80] An important note is that this was a result of the debasement of their currency.[81]

Like other research that has explored long waves, periods of economic downturns are generally viewed as a catalyst for technological innovation, which occur in clusters near the end (or beginning) of each wave.[56] The author postulates that this is a result of human necessity to become more resourceful during periods of tight credit, and is speculated to be correlated to communities developing closer bonds due to hardship.[82]

It was during this period of economic downturns that witnessed the rise of the first mechanical computing devices. There are generally two individuals who are credited with the development of the first arithmetic machines, or mechanical computing devices. Although it could be argued that these origins went back to the Abacus in the far-east, and even Galileo’s sector.[83] Wilheim Schickard, a friend and colleague of Johannes Kepler, is believed to have developed the first mechanical computing device for Kepler’s calculations, but was destroyed in a 1624 fire.[84] Kepler, at that same time had developed the first table of logarithms.[85] The world had to wait almost two decades longer before the first working prototypes of the mechanical computer emerge from the mind of Blaine Pascal.[86] While several examples are still in existence today, these devices had practical limitations that restricted their widespread utility, along with the high cost of production.[87] They did; however, help initiate an era of more rapid computation, and likely had modest effects on certain industries such as science, engineering, construction, banking, and insurance.[88] But more importantly these devices led to technological advances that had far greater practical use cases, starting with the Leibniz wheel later that century, eventually leading to the analytical engines developed two centuries later. The author acknowledges that there are limited historical reference points to the direct impact of these mechanical computers, outside of the historical timeline for computing in general.

The downturn of the second wave was characterized by bloody warfare throughout the western world. These conflicts included the Revolutionary War in the British colonies of the Americas, the Napoleonic Wars, the War of 1812, and ending with the American Civil War in the middle of the 19th century. Some authors have argued that these wars were directly correlated to inflationary policies of the Bank of England at that time.[89] Indeed, the Bank of England was the institute that began the large-scale use of promissory notes in the western world,[90] eventually abandoning the gold standard at the end of the 18th century, replacing it with demand-side inflationary models that resemble modern Keynesian policies. These large monetary deficits run by the Bank of England were shown to correlate with years of war, allowing for boom-bust cycles all throughout the 18th century that were previously detailed in the work of Stanley M. Jevons.[29]

At the end of these conflicts emerged a cluster of innovation relating to the first analytical engines produced by Charles Babbage,[91] as well as the first telegraphs which were made famous by Samuel Morse. The telegraph has long been argued to have caused the phenomenon we refer to as globalization,[92] ultimately leading to the internet.[93] The telegraph catalyzed many additional inventions of great significance during this era, including the expansion of the railroads,[94] the beginning of the telephone,[95] as well as having profound implications for the eventual widespread use of electricity.[96]

The downturn of the third wave was characterized by a combination of the large-scale global conflicts of World Wars I and II, in addition to the bank panics of 1901[97] and 1907,[98] and eventually the great depression, characterized as the worst systemic banking crisis of the 20th century.[99] It has been argued that the great depression partly stemmed from the rapid technological changes being imposed upon the banking industry, causing it to quickly become overbuilt.[100] The ending of the third wave and beginning of the fourth coincides with a cluster of innovation concerning modern electro- mechanical computers. These inventions are known to have been inspired by the second World War. In 1937, Alan Turing developed what became known as the Turing machine in an effort to decode messages sent from German Enigma machines during the war effort.[101] These inventions initiated the fourth wave of coding and also brought the world to an international gold standard through the Bretton Woods agreement.[102] This period has been characterized as a golden-age for many, with virtually no banking crises through its duration.[91] The author acknowledges; however, that this also coincides with the positive trajectory of the fourth wave, where banking crises have been historical shown to be minimal. The Bretton Woods agreement was abolished when Richard Nixon directed his Treasury Secretary to suspend the inter-convertibility of the US dollar to gold in August 1971, in order to create “a new prosperity without war.”[103] The next two decades were characterized by sustained global conflicts and economic hardships: including the oil crisis of 1973,[104] the stagflation of the 1970s,[105] and eventually leading to Black Monday in October 1987 and the Persian Gulf wars of the early 1990s. It has been argued by many authors that Black Monday was a direct consequence of the high-frequency trading algorithms stemming from advances in computing (or coding) technology.[106] Additionally, Japan experienced one of the worst asset bubbles through history, culminating in the collapse of their stock market and commodity prices in the late 1980s and early 1990s.[107]

In the backdrop of the 1970s and 80s, there was a new technology on the horizon. This is characterized by what we know today as the internet. The concept of ARPANET was first published by Lawrence G. Roberts[108] and ultimately led to the first internet protocol standards based on packet switching (TCP/IP) getting deployed in 1983, which eventually led to the World Wide Web (WWW) being formed in the early to mid 1990s.[109] This cycle produced the largest market bubble (tech bubble) since the great depression (in inflation-adjusted value),[110] where the Nasdaq Index rose to nearly 4700 (in real terms) in February 2000, before declining to approximately 1200 in September 2002, or a percentage decline of roughly 75%. As argued in the previous section, this theory supposes that the markets have an absolute maximum for each cycle that are relative to one another. It should be noted that all the way back to the early studies in economic cycles, nearly all early researchers recognized and approximated boom-and- bust cycles as occurring approximately every ten years. The downturn of the fifth wave started with the dot-com bust of the early 2000s,[111] with other events including the September 11th, 2001 attacks that ended up leading to the conflicts in Afghanistan and Iraq,[112] and ended with the subprime mortgage crisis (2006-2008) in the United States that nearly brought down the entire global economic system.[113]

During this period of economic turmoil, the newest wave (sixth wave) of coding technology was coming onto the scene. This is what has become known as cloud and mobile technologies. Cloud computing was first conceptualized back in the late 1960s, but commercialized by Amazon in 2006, leading to widespread deployment by the early 2010s.[114] This distributed computing paradigm can also be thought to be intrinsically linked with the adoption of mobile devices, as well as the advancement of blockchain technology, which emerged shortly after the deployment of consumer cloud services.[115] The past ten years has witnessed dramatic growth in asset prices all around the world, with major US stock indices, on average increasing greater than 300% over the ten year span of 2009-2018 (detailed in the previous section). Based on the theory presented in this work, the peak of the sixth wave has already been reached (based on the absolute maximum of the wave) and is currently entering a period of economic downturn which will culminate in some large economic collapse before the end of 2020.

It is hypothesized that the seventh, and possibly final wave of this proposed economic super-cycle will be the result of artificial intelligence, which will follow an almost precise pattern that every previous wave has followed, with average global asset values approximately doubling from their recent maximums in the short window between 2020 and ~2025.

Conclusions

This in-depth work has taken on a myriad of different topics, attempting to blend the realities from the natural sciences, social sciences, even a spin toward universal understandings. It is intended to serve as a framework for discussion, such that we may explore possibilities of using the idea that the economy is a natural system in an effort to reconsider the human-centric economic system of present.

The author has attempted to present the most clear and concise understanding of this system that he has to present date, and hopes to see this work be the basis for additional analysis and discussion. We develop scientific theories to help us understand the world around us, and by doing so, hope to make the world a better place for everyone.

It is best to end with the quote of one of the best known scientists and thinkers of the 20th century, Albert Einstein, who was attributed as saying

“All great achievements in science start from intuitive knowledge, namely, in axioms, from which deductions are then made. ... Intuition is the necessary condition for the discovery of such axioms.”[116]

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